4.7 Article

Expression profiling of microRNAs by deep sequencing

Journal

BRIEFINGS IN BIOINFORMATICS
Volume 10, Issue 5, Pages 490-497

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbp019

Keywords

deep sequencing; expression profiling; microRNA

Funding

  1. Ovarian Cancer Research
  2. National Institutes of Health [P30 CA125123]
  3. Dan L. Duncan Cancer Center at Baylor College of Medicine

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MicroRNAs are short non-coding RNAs that regulate the stability and translation of mRNAs. Profiling experiments, using microarray or deep sequencing technology, have identified microRNAs that are preferentially expressed in certain tissues, specific stages of development, or disease states such as cancer. Deep sequencing utilizes massively parallel sequencing, generating millions of small RNA sequence reads from a given sample. Profiling of microRNAs by deep sequencing measures absolute abundance and allows for the discovery of novel microRNAs that have eluded previous cloning and standard sequencing efforts. Public databases provide in silico predictions of microRNA gene targets by various algorithms. To better determine which of these predictions represent true positives, microRNA expression data can be integrated with gene expression data to identify putative microRNA:mRNA functional pairs. Here we discuss tools and methodologies for the analysis of microRNA expression data from deep sequencing.

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